The bioeconomy, utilizing biological resources for various products, aims for sustainable resource use. However, its sustainability is not inherent, and environmental impacts like land use change, increased water use, and greenhouse gas emissions must be monitored. Existing footprint approaches assess environmental impacts, but water pollution's contribution to clean freshwater scarcity remains under-researched. This study addresses this gap by introducing a water quality footprint indicator, based on virtual dilution volume (VDV), to quantify agricultural water pollution from nitrogen (N), phosphorus (P), and glyphosate (G) emissions. This complements the established footprint monitoring framework for the German bioeconomy. The VDV represents the virtual volume of water needed to dilute pollution below specified thresholds. This volumetric approach allows comparison with quantitative water use and facilitates assessment of regional clean water scarcity using existing water stress indicators. The key difference from existing grey water footprint approaches lies in defining dilution using demineralized water to reach naturally occurring background concentrations (for N and P) or target concentrations (for G) from the WHO drinking water standards, irrespective of the pre-existing water quality of the basin.

Existing literature extensively covers grey water footprint approaches, focusing on expressing water pollution volumetrically by dividing substance loads by threshold values derived from water quality standards. However, previous studies often used regionally available water for dilution, rather than demineralized water. The water scarcity footprint concept, used here as a basis, takes a catchment-wide perspective, viewing water bodies as a hydrological unit. This addresses the fact that water use from any compartment can contribute to regional scarcity. Prior research has also analyzed global nitrogen and phosphorus loads from agriculture, but a comprehensive assessment integrating water pollution with water stress levels for the specific context of the German bioeconomy is lacking. This study fills that gap.

The study calculates the water quality footprint in three steps: 1. **VDV Calculation:** The VDV concept is extended to express agricultural water pollution per country. Using data from IMAGE-GNM (for N and P), PEST-CHEMGRIDS (for G application rates), and USEtox (for G mass fraction), the VDV is calculated by dividing emissions (load_i,em) by the geogenic background concentration (C_geos,i) for N and P or the target concentration (C_targe,i) for G. Local conditions influencing emissions are considered. The largest VDV represents the country's water quality footprint, accounting for country water stress levels. 2. **Raw Material Input Determination:** Raw material input into the German bioeconomy (RMI) is obtained from the EXIOBASE multi-regional input-output table for 1995 and 2020. Country-level resolution for EXIOBASE rest-of-world regions is achieved using FAOSTAT data. Total agricultural water quality footprints are multiplied by the share of agricultural raw materials exported to Germany. 3. **Footprint Presentation:** The German water quality footprint is presented in m³ per German inhabitant for 1995 and 2020, alongside country water stress levels calculated using a withdrawal-to-availability ratio (WTA) based on AQUASTAT data. Glyphosate results are presented only for 2020 due to data limitations. The N load is calculated from a cropland mass balance, considering fertilizer input, livestock excretions, deposition, fixation, harvest, volatilization, soil loss, denitrification, and emissions to surface and groundwater. P load considers only surface runoff emission, neglecting groundwater emission. G load is calculated from application rates and a mass fraction from USEtox, considering biodegradation, sorption, and leaching. Geogenic background concentrations for N and P are compiled from literature; the target concentration is from WHO drinking water standards. The virtual dilution volume is categorized as low, medium, or high based on comparison with German direct drinking water withdrawal. Although recommended, the study refrains from using AWARE water stress factors due to data limitations, using own WTA calculation with AQUASTAT data instead. Weighting is not employed due to the study scope. The calculated dilution volume is presented in m³ per inhabitant of Germany.

In 2020, the total virtual water volume needed to dilute water pollution from agricultural production for the German bioeconomy was 4000 Gigacubic meters (90 times Lake Constance's volume). Domestic German production accounted for 22% (20 times Lake Constance's volume). Compared to 1995, the total volume increased by one-third, while the share of domestic production decreased by 16%. Germany's water quality footprint was high in 49 countries in 2020. Domestic production had the largest footprint (approximately 14,000 m³ per German inhabitant, 300 times the German direct drinking water withdrawal). Brazil and China followed. In most countries, footprints exceeded German direct drinking water withdrawal. While many countries were European, countries from all continents were represented. Several countries with high footprints (e.g., China, Spain, India) exhibited medium water stress. The study notes that virtual dilution volumes are theoretical, not actually consumed. However, they indicate clean water scarcity. These volumes can be orders of magnitude higher than actual water withdrawal. In most countries, dilution volume exceeded irrigation water withdrawals by a factor of over 100. In almost all countries, phosphorus was responsible for the highest dilution volume due to a lower geogenic background concentration compared to nitrogen and lower application compared to glyphosate. Severe hotspots (high water stress and high dilution volumes) included Iran, Spain, Turkey, India, and China. The German water quality footprint increased considerably worldwide between 1995 and 2020, particularly evident in India. A shift in supply sources was also observed (e.g., Mexico and Netherlands). A comparison with crop yields revealed that in several African, Asian, and Pacific countries, fertilizer and pesticide use strongly increased without proportional yield increases. This suggests potential environmental problems with German involvement. Comparing agricultural virtual dilution volume to water availability reveals that in some countries virtual dilution for agricultural pollution alone exceeds water availability, more pronounced in 2020 compared to 1995. The study also performed a sensitivity analysis, revealing high sensitivity of the dilution volume to changes in geogenic background and target concentrations, especially negative changes.

The findings demonstrate that German water quality footprints abroad are significantly high, exceeding German direct water use dramatically. They often exceed irrigation water withdrawals in exporting countries, indicating that water pollution contributes more to clean water scarcity than direct water abstraction. The analysis of water quality footprints, including water stress levels, identified hotspots of clean water scarcity (India, Spain, China, Iran, Pakistan). The increase in water quality footprints worldwide between 1995 and 2020, particularly in India, reflects increased fertilizer and pesticide use and shifts in supply sources. The comparison of dilution volumes and crop yields revealed that increasing fertilizer and pesticide use in several African, Asian, and Pacific countries did not proportionally increase yields, indicating potential environmental harm with German involvement. The country-level resolution of the analysis, chosen due to data limitations and the need to balance spatial resolution with uncertainty, may mask regional water stress variations. The study's reliance on advanced models and maps accounts for the high spatial dependence of emissions, despite presenting country-level results. However, uncertainties remain, particularly regarding glyphosate emissions and geogenic background concentrations. The study suggests that the water quality footprint can be a valuable indicator for national monitoring, identifying and monitoring points in the supply chain where water pollution is most significant.

This study introduces a water quality footprint indicator to assess the impact of German bioeconomy on global water resources. The findings highlight significant water pollution associated with agricultural production supporting the German bioeconomy, particularly in specific countries facing water stress. Further research should refine spatial and temporal resolution, incorporate a broader range of pesticides, and improve data accuracy to reduce uncertainties. This improved understanding will contribute to more sustainable practices and policy development.

The study's main limitations include the country-level spatial resolution, potentially masking regional variations in water stress; the focus on a limited set of pesticides, potentially underestimating the overall impact; and uncertainties inherent in the global analysis, particularly concerning data gaps and assumptions in global models and maps used for calculations. The temporal resolution is also limited, using only two points in time to assess the changes. Future studies would benefit from higher spatial and temporal resolution, more detailed pesticide data, and continuous improvement of the data base.